Integrate Paypal Expanded Checkou to a wordpress plugin

25.0 USD

25.0 USD peopleperhour 技术与编程 海外
1天前

详细信息

I'm looking for a skilled developer to help me integrate the expanded PayPal checkout into my open-source WordPress hotel booking plugin. This should include all the payment options that PayPal supports, such as Venmo, Debit/Credit cards, and PayPal Credit.
Key requirements:- Full integration of PayPal, Venmo, Debit/Credit Card, and PayPal Credit into the booking plugin.- Improving the calendar synchronization of the plugin.- Adding booking notifications functionality.
I need this completed within 5 days. Please note that I will not release the funds until I receive a video showing the integration working properly and the calendar is synced whenever a payment is captured. Ideal candidates should have substantial experience with WordPress plugin development and PayPal integration.
The plugin is Vikbooking search for it available on wordpress.org If you can contact me and start proposal with X in start and L at the end

免责声明

该外包需求信息来源于站外平台,本站仅提供公开信息部分字段展示与订阅服务,更多请查看免责声明

关注公众号,不定期副业成功案例分享
关注公众号

不定期副业成功案例分享

领先一步获取最新的外包任务吗?

立即订阅

类似推荐

Ai automated editorial system Overview of the System: To automate the process of identifying key news stories and economic events, then finding relevant academic experts for interviews, we need a structured workflow with three core components: 1. News Feed Monitoring & Story Extraction Objective: Scrape or fetch top stories daily from major news sources (BBC, FT, NYT). Identify the most relevant 10 stories for academic discussions. Extract key details (headline, summary, category, and related experts). Process: News Scraping & API Integration: Use RSS feeds or news APIs (BBC News API, NYT API, FT API) to pull daily stories. https://www.bbc.co.uk/news/10628494 https://developer.nytimes.com/apis Apply NLP (Named Entity Recognition, NER) to extract topics, locations, and institutions Story Selection & Categorization: Use an LLM or rule-based filtering to: Select 10 most relevant stories daily. Categorize them (Politics, Science, Economics, Law, etc.). Finding Relevant Academics: Search Semantic Scholar, OpenAlex, ArXiv, CORE, or university directories /our own databases for 5 academic experts per story. Prioritize experts based on: Their recent papers on similar topics. GET THEIR emails. Output & Storage: Generate a structured daily report (JSON) with: Story headlines & summaries. Academic expert details (Name, Affiliation, Contact, Paper Links). 5. Send automated email drafts to invite experts DAILY. 2. Economic Calendar Event Monitoring Objective: Track major global economic events (UK, EU, US, Asia). Extract upcoming financial events (e.g., interest rate decisions, GDP releases). Find experts to analyze these events. Process: Data Sources & Event Monitoring: Integrate economic calendar APIs (ForexFactory, Investing.com, TradingEconomics, FRED). Fetch major scheduled events: Monetary policy meetings (Fed, ECB, BoE, BoJ, PBoC). GDP, inflation, employment reports. Market-moving events (OPEC meetings, IMF/World Bank reports). Event Categorization & Prioritization: Use event scoring based on: Global impact. Historical volatility caused by similar events. News coverage sentiment. Finding Academic Experts: Identify economists, financial analysts, and policy researchers via: University economics departments. Central bank research papers. Financial market analysis reports. Output & Storage: Generate a daily/weekly report with: Event summary. Impact analysis. 5 expert contacts for interviews. Automate email drafts for outreach. 3. Automation & Execution Plan Technology Stack Data Collection: RSS Feeds, APIs (News & Economic Calendar). Processing: Python (Pandas, NLP, Scraping). Storage: Google Sheets / Database. Expert Search: OpenAlex, Semantic Scholar, University Directories. Email Automation: Google Workspace API (Gmail), Mail Merge. Scaling & Refinement Phase 1: Automate daily reports (news + economic events) and manually review expert selection. Phase 2: Automate expert filtering with relevance scoring. Phase 3: Fully automate outreach emails with AI-generated pitch drafts.
60.0 GBP 技术与编程 peopleperhour 海外
20小时前